2015
DOI: 10.1109/tpwrd.2015.2422139
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Variable Forgetting Factor Recursive Least Square Control Algorithm for DSTATCOM

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Cited by 102 publications
(26 citation statements)
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References 27 publications
(28 reference statements)
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“…In this regard, a large forgetting factor should be assigned to the parameters changing slowly to guarantee the stability of the algorithm, while a small forgetting factor is more appropriate for the tracking of fast varying parameter. In seeking to address this problem, the VFFRELS with multiple forgetting factors [41][42][43] for identification is applied in this paper. With the VFFRELS, the forgetting factors can be decoupled and tuned separately to improve the parameters stability and tracking accuracy of SOC estimation.…”
Section: Parameters Identificationmentioning
confidence: 99%
“…In this regard, a large forgetting factor should be assigned to the parameters changing slowly to guarantee the stability of the algorithm, while a small forgetting factor is more appropriate for the tracking of fast varying parameter. In seeking to address this problem, the VFFRELS with multiple forgetting factors [41][42][43] for identification is applied in this paper. With the VFFRELS, the forgetting factors can be decoupled and tuned separately to improve the parameters stability and tracking accuracy of SOC estimation.…”
Section: Parameters Identificationmentioning
confidence: 99%
“…Digital filters can be divided into recursive and non-recursive ones [25], [26]. A non-recursive filter sums up a certain number of input values.…”
Section: Digital Filter Basicsmentioning
confidence: 99%
“…Shunt compensator provides suitable load compensation to prevent distorted currents entering the utility grid. Also, there is an increased interest in the development of advanced and fast digital control algorithms to achieve the desired power quality standards.…”
Section: Introductionmentioning
confidence: 99%
“…Advanced soft computing controllers based on artificial neural network, 7-9 fuzzy techniques, 10 adaline, 11 and adaptive neuro fuzzy inference system 12,13 are interesting but complex. Recently, a number of new controllers [14][15][16][17][18][19] based on repetitive computation and updating of weights such as anti Hebbian, 14 least means square-based technique, 15 adaptive notch-based control 16 and recursive techniques, 17,18 and other signal cancelation techniques 19 have gained immense popularity. The desired controller should have the following objectives--ability to perform precise reference tracking, simple computational demands, and low parametric sensitivity.…”
Section: Introductionmentioning
confidence: 99%